Triple
T27406173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katsushika Ward |
E692004
|
entity |
| Predicate | belongsToFireDepartment |
P183983
|
FINISHED |
| Object | Tokyo Fire Department |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Tokyo Fire Department | Statement: [Katsushika Ward, belongsToFireDepartment, Tokyo Fire Department]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToFireDepartment Context triple: [Katsushika Ward, belongsToFireDepartment, Tokyo Fire Department]
-
A.
officersServeIn
Indicates that certain officers perform their duties or hold positions within a specified organization, unit, or jurisdiction.
-
B.
hasChiefFireOfficer
Indicates that an entity has, is associated with, or is overseen by a specific chief fire officer.
-
C.
associatedWithLawEnforcementAgency
Indicates that an entity has a formal connection, role, or involvement with a law enforcement agency.
-
D.
isPartOfLawEnforcementSystem
Indicates that an entity belongs to, operates within, or functionally contributes to a law enforcement system or framework.
-
E.
isMilitaryStaffOf
Indicates that one entity serves as military personnel working for, or assigned to, another entity (such as an organization, unit, or individual).
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ef5205fc808190ad3efc5525b8e6d6 |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f7aaabb58c8190bf81673608ecfb6e |
completed | May 3, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69f7a8cec6d48190bebfa884b2f938c0 |
completed | May 3, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f7aa6795f481908940838ee7041ff5 |
completed | May 3, 2026, 8:04 p.m. |
Created at: April 27, 2026, 12:30 p.m.